1. Field of the Invention
The present invention relates generally to a voice signal detection system and method, and in particular, to a voice signal detection system and method for detecting a voice signal using peak information in a time axis.
2. Description of the Related Art
There has been a recent increase in the development of systems using voice signals, to perform processes such as coding, recognition and strengthening, based on the voice signal. Accordingly, methods of accurately detecting the voice signal have been increasingly researched.
Two conventional methods of detecting a voice signal are a method using energy of an input signal and a method using a zero crossing rate. The method using energy is a method of measuring energy of an input signal and detecting a portion in which measured energy is high as a voice signal if the measured energy value is high. The method using a zero crossing rate is a method of measuring a zero crossing rate of an input signal and detecting a portion thereof which is high as a voice signal. Recently, to increase accuracy of voice signal detection, a method of combining the two methods has also been being frequently used.
The two above-described methods have low accuracy in a state where noise is included in an input signal. For example, since the method of detecting a portion in which a measured energy value is high as a voice signal does not consider energy due to noise, if the energy due to noise is high, a noise signal may be recognized as a voice signal, and vice versa.
In addition, since the method of detecting a portion in which a zero crossing rate is high as a voice signal cannot determine whether zero crossing occurs by a noise signal or a voice signal, if the zero crossing rate is high due to the noise signal, the noise signal may be recognized as the voice signal, and vice versa.
In the above methods, a noise signal recognized as a voice signal is called an additive error, and a voice signal recognized as a noise signal is called as a subtractive error. For the additive error, a noise signal can be cancelled through an additional process. However, for the subtractive error, since a voice signal has been already recognized as a noise signal and cancelled, the voice signal cannot be recovered in most cases. Thus, a voice detection technique for fundamentally preventing the subtractive error is required.
In addition, most of the conventional voice signal detection methods detect a voice signal in a frame unit. In this case, even if an error occurs in a unit smaller than the frame unit, the error is recognized as an error of a frame unit. In addition, since the above-described conventional voice signal detection methods detect a voice signal using a fixed method, if a determined algorithm fails, an error due to the failure is transferred to a process of a subsequent stage, thereby causing multiple errors.